Clay Shirky on Mega-Universities and Scale— from philonedtech.com by Clay Shirky[This was a guest post by Clay Shirky that grew out of a conversation that Clay and Phil had about IPEDS enrollment data. Most of the graphs are provided by Phil.]

Excerpts:

Were half a dozen institutions to dominate the online learning landscape with no end to their expansion, or shift what Americans seek in a college degree, that would indeed be one of the greatest transformations in the history of American higher education. The available data, however, casts doubt on that idea.

Though much of the conversation around mega-universities is speculative, we already know what a mega-university actually looks like, one much larger than any university today. It looks like the University of Phoenix, or rather it looked like Phoenix at the beginning of this decade, when it had 470,000 students, the majority of whom took some or all of their classes online. Phoenix back then was six times the size of the next-largest school, Kaplan, with 78,000 students, and nearly five times the size of any university operating today.

From that high-water mark, Phoenix has lost an average of 40,000 students every year of this decade.

From DSC:First of all, I greatly appreciate both Clay’s and Phil’s thought leadership and their respective contributions to education and learning through the years. I value their perspectives and their work. Clay and Phil offer up a great article here — one worth your time to read.

The article made me reflect on what I’ve been building upon and tracking for the last decade — a next generation ***PLATFORM*** that I believe will represent a powerful piece of a global learning ecosystem. I call this vision, “Learning from the Living [Class] Room.” Though the artificial intelligence-backed platform that I’m envisioning doesn’t yet fully exist — this new era and type of learning-based platform ARE coming. The emerging signs, technologies, trends — and “fingerprints”of it, if you will — are beginning to develop all over the place.

Such a platform will:

Be aimed at the lifelong learner.

Offer up major opportunities to stay relevant and up-to-date with one’s skills.

Offer access to the program offerings from many organizations — including the mega-universities, but also, from many other organizations that are not nearly as large as the mega-universities.

Be reliant upon human teachers, professors, trainers, subject matter experts, but will be backed up by powerful AI-based technologies/tools. For example, AI-based tools will pulse-check the open job descriptions and the needs of business and present the top ___ areas to go into (how long those areas/jobs last is anyone’s guess, given the exponential pace of technological change).

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Below are some quotes that I want to comment on:

Not nothing, but not the kind of environment that will produce an educational Amazon either, especially since the top 30 actually shrank by 0.2% a year.

Instead of an “Amazon vs. the rest” dynamic, online education is turning into something much more widely adopted, where the biggest schools are simply the upper end of a continuum, not so different from their competitors, and not worth treating as members of a separate category.

Since the founding of William and Mary, the country’s second college, higher education in the U.S. hasn’t been a winner-take-all market, and it isn’t one today. We are not entering a world where the largest university operates at outsized scale, we’re leaving that world;

From DSC:I don’t see us leaving that world at all…but that’s not my main reflection here. Instead, I’m not focusing on how large the mega-universities will become. When I speak of a forthcoming Walmart of Education or Amazon of Education, what I have in mind is a platform…not one particular organization.

Consider that the vast majority of Amazon’s revenues come from products that other organizations produce. They are a platform, if you will. And in the world of platforms (i.e., software), it IS a winner take all market.

“In the software world, particularly for platforms, these are winner-take-all markets.

So it’s all about a forthcoming platform — or platforms. (It could be more than one platform. Consider Apple. Consider Microsoft. Consider Google. Consider Facebook.)

But then the question becomes…would a large amount of universities (and other types of organizations) be willing to offer up their courses on a platform? Well, consider what’s ALREADY happening with FutureLearn:

Finally…one more excerpt from Clay’s article:

Eventually the new ideas lose their power to shock, and end up being widely copied. Institutional transformation starts as heresy and ends as a section in the faculty handbook.

From DSC:This is a great point. Reminds me of this tweet from Fred Steube (and I added a piece about Western Telegraph):

One of the first levels of opportunity is simply embedding the skills that are demanded in the job market into educational programs. Education certainly has its own merits independent of professional outcomes. But critics of higher education who suggest graduates aren’t prepared for the workforce have a point in terms of the opportunity for greater job market alignment, and less of an “ivory tower” mentality at many institutions. Importantly, this does not mean that there isn’t value in the liberal arts and in broader ways of thinking—problem solving, leadership, critical thinking, analysis, and writing are among the very top skills demanded by employers across all educational levels. These are foundational and independent of technical skills.

The second opportunity is building an ecosystem for better documentation and sharing of skills—in a sense what investor Ryan Craig has termed a “competency marketplace.” Employers’ reliance on college degrees as relatively blunt signals of skill and ability is partly driven by the fact that there aren’t many strong alternatives. Technology—and the growth of platforms like LinkedIn, ePortfolios and online assessments—is changing the game. One example is digital badges, which were originally often positioned as substitutes to degrees or certificates.

Instead, I believe digital badges are a supplement to degrees and we’re increasingly seeing badges—short microcredentials that discretely and digitally document competency—woven into degree programs, from the community college to the graduate degree level.

However, it is becoming increasingly clear that the market is demanding more “agile” and shorter-form approaches to education. Many institutions are making this a strategic priority, especially as we read the evolution of trends in the global job market and soon enter the 2020s.

Online education—which in all its forms continues to slowly and steadily grow its market share in terms of all higher ed instruction—is certainly an enabler of this vision, given what we know about pedagogy and the ability to digitally document outcomes.

In addition, 64 percent of the HR leaders we surveyed said that the need for ongoing lifelong learning will demand higher levels of education and more credentials in the future.

AbstractThe EDUCAUSE Horizon Report Preview provides summaries of each of the upcoming edition’s trends, challenges, and important developments in educational technology, which were ranked most highly by the expert panel. This year’s trends include modularized and disaggregated degrees, the advancing of digital equity, and blockchain.

For more than a decade, EDUCAUSE has partnered with the New Media Consortium (NMC) to publish the annual Horizon Report – Higher Education Edition. In 2018, EDUCAUSE acquired the rights to the NMC Horizon project.

CONCLUSION
This paper has outlined the plethora of new credential types, uses, and modes of delivery. It also has highlighted advancements in assessment. In terms of assessment content, the progression of mastery-based assessments is a distinct departure from the traditional knowledge-based assessment approaches. New assessments are likely to enter the market, as companies see the tremendous growth of competency-based assessments that will be critical and necessary in the future ecosystem described.

Assessments are no longer just a source of grades for gradebooks. They have forged two meaningful bypass routes to seat time in higher education. In the first, competency-based education assessments gate the pace of student progress through the curriculum. In the second, certification by an exam delivers not a grade, but a degree-like credential in a relevant occupation, indicating skill and expertise. For some occupations, this exam-as-credential has already been market validated by employers’ willingness to require it, hire by it, and pay a salary premium for it.

All of these innovations are driving towards a common end. The future learning-to employment ecosystem will be heavily reliant on credentials and assessments. We see:

A future in which credentials will no longer be limited to degrees, but will come in varying shapes and sizes, offered by many organizations, training providers, and employers;

A future in which credentials will, however, be able to articulate a set of underlying “know” knowledge and “do” performance skill competencies;

A future in which a credential’s scope will be described by the set of competencies it covers, and measured via assessment;

A future in which a credential’s quality will be indicated by evidence of mastery within each competency before it is awarded;

A future in which quality metrics, such as consumer reviews or employer use of credentials will come into play, bringing the best and most usable credentials and assessments to the forefront.

And, finally, the future ecosystem will depend heavily on online and technology-enabled strategies and solutions. The working learner will turn away from those stringent solutions that require seat time and offer little flexibility. They will drive the market hard for innovations that will lead to consumer-facing marketplaces that allow them a “one-stop shop” approach for working, learning, and living.

The massive market of the working learner/the learning worker is here to stay. The future is that learner. Credentials and assessment will find their own strong footing to help successfully meet both the learners’ needs and the employers’ needs. We applaud this SHIFT. For, it will be an ecosystem that services many more learners than today’s education to employment system serves.

Most coherent report I have read on the erosion of degrees and the rise of assessing-for-work and amassing certifications as the competencies for the modern workplace. Jamai Blivin, ofwww.innovate-educate.org, and Merrilea Mayo, of Mayo Enterprises, have put in one report the history, current trends and the illogic for many people of paying for a retail bachelor’s degree when abundant certifications are beginning to prove themselves. Workforce and community colleges, this is a must-read. Kudos!

The top learning trend in K-12 learning in 2018 was active learning spaces–from double classrooms in old buildings from California’s Central Valley to the west tip of Texas in El Paso and multiage pods in new spaces from Redwood City to Charlottesville.

The flexible spaces facilitate project-based learning and competency-based progressions. Students move from project teams to skill groups to activity centers building skills and developing agency and self-management.

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Competency: The Trend to Watch in 2019A year from now people will be talking about competency frameworks–how learners progress as they demonstrate mastery.

The shift from marking time to measuring learning will be generational in length, but our landscape analysis suggests several interesting signs of progress that will be evident in 2019:

In the most interesting merger of the year, LRNG, the leading youth badging platform, joined forces with SNHU, the leading online university. Look for badges capturing in and out of school learning that stack into college credit.

More schools, like Purdue Polytech, will embrace project-based learning and competency-based progressions with support from XQ, NGLC funds, and NewSchools Venture Fund.

More platform partnerships where districts/networks are working in development cycles with platform providers (e.g. Brooklyn LAB and Cortex, Purdue Polytech and Course Networking, Lindsay USD and Empower).

More artificial intelligence is showing up in learning platforms improving personalization, formative feedback, and student scheduling.

More demand for interoperability will be evident as a result of efforts like Project Unicorn.

It’s going to be a good new year. Find a couch or pull up a bar stool–your choice. Work on a badge or microcredential, it’s likely to be more widely recognized next year.

Brickstuff is the perfect way to light up Lego builds. This starter kit includes everything you need to get started. No electronics or soldering knowledge is necessary to set up these lights and start using them right away. Each flexible 2-LED Light Strip has a self-adhesive backing, which allows easy mounting to almost any surface. The strips are flexible, allowing you to mount them even on curved surfaces. This kit also includes a battery pack, so you can be up and running right away. This kit is ready to use with any microcontroller or robotics project too.

A few years ago, in a move toward professional learning, LinkedIn bought Lynda.com for $1.5 billion, adding the well-known library of video-based courses to its professional social network. Today LinkedIn officials announced that they plan to open up their platform to let in educational videos from other providers as well—but with a catch or two.

The plan, announced Friday, is to let companies or colleges who already subscribe to LinkedIn Learning add content from a select group of other providers. The company or college will still have to subscribe to those other services separately, so it’s essentially an integration—but it does mark a change in approach.

For LinkedIn, the goal is to become the front door for employees as they look for micro-courses for professional development.

LinkedIn also announced another service for its LinkedIn Learning platform called Q&A, which will give subscribers the ability to pose a question they have about the video lessons they’re taking. The question will first be sent to bots, but if that doesn’t yield an answer the query will be sent on to other learners, and in some cases the instructor who created the videos.

LinkedIn has become quite a juggernaut in the corporate learning market. Last time I checked the company had more than 17 million users, 14,000 corporate customers, more than 3,000 courses and was growing at high double-digit rates. And all this in only about two years.

And the company just threw down the gauntlet; it’s now announcing it has completely opened up its learning platform to external content partners. This is the company’s formal announcement that LinkedIn Learning is not just an amazing array of content, it is a corporate learning platform. The company wants to become a single place for all organizational learning content.

LinkedIn now offers skills-based learning recommendations to any user through its machine learning algorithms.

Is there demand for staying relevant? For learning new skills? For reinventing oneself?

From DSC:So…look out higher ed and traditional forms of accreditation — your window of opportunity may be starting to close. Alternatives to traditional higher ed continue to appear on the scene and gain momentum. LinkedIn — and/or similar organizations in the future — along with blockchain and big data backed efforts may gain traction in the future and start taking away some major market share. If employers get solid performance from their employees who have gone this route…higher ed better look out.

Meet the 83-Year-Old App Developer Who Says Edtech Should Better Support Seniors — from edsurge.com by Sydney JohnsonExcerpt (emphasis DSC):
Now at age 83, Wakamiya beams with excitement when she recounts her journey, which has been featured in news outlets and even at Apple’s developer conference last year. But through learning how to code, she believes that experience offers an even more important lesson to today’s education and technology companies: don’t forget about senior citizens.Today’s education technology products overwhelmingly target young people.And while there’s a growing industry around serving adult learners in higher education, companies largely neglect to consider the needs of the elderly.

Amazon loves to use the word flywheel to describe how various parts of its massive business work as a single perpetual motion machine. It now has a powerful AI flywheel, where machine-learning innovations in one part of the company fuel the efforts of other teams, who in turn can build products or offer services to affect other groups, or even the company at large. Offering its machine-learning platforms to outsiders as a paid service makes the effort itself profitable—and in certain cases scoops up yet more data to level up the technology even more.

It took a lot of six-pagers to transform Amazon from a deep-learning wannabe into a formidable power. The results of this transformation can be seen throughout the company—including in arecommendations system that now runs on a totally new machine-learning infrastructure.Amazon is smarter in suggesting what you should read next, what items you should add to your shopping list, and what movie you might want to watch tonight. And this year Thirumalai started a new job, heading Amazon search, where he intends to use deep learning in every aspect of the service.

“If you asked me seven or eight years ago how big a force Amazon was in AI, I would have said, ‘They aren’t,’” says Pedro Domingos, a top computer science professor at the University of Washington. “But they have really come on aggressively. Now they are becoming a force.”

Maybe the force.

From DSC:When will we begin to see more mainstream recommendation engines for learning-basedmaterials? With the demand for people to reinvent themselves, such a next generation learning platform can’t come soon enough!

Turning over control to learners to create/enhance their own web-based learner profiles; and allowing people to say who can access their learning profiles.

AI-based recommendation engines to help people identify curated, effective digital playlists for what they want to learn about.

Voice-driven interfaces.

Matching employees to employers.

Matching one’s learning preferences (not styles) with the content being presented as one piece of a personalized learning experience.

From cradle to grave. Lifelong learning.

Multimedia-based, interactive content.

Asynchronously and synchronously connecting with others learning about the same content.

Online-based tutoring/assistance; remote assistance.

Reinvent. Staying relevant. Surviving.

Competency-based learning.

We’re about to embark on a period in American history where career reinvention will be critical, perhaps more so than it’s ever been before. In the next decade, as many as 50 million American workers—a third of the total—will need to change careers, according to McKinsey Global Institute. Automation, in the form of AI (artificial intelligence) and RPA (robotic process automation), is the primary driver. McKinsey observes: “There are few precedents in which societies have successfully retrained such large numbers of people.”

Online learning continues to expand in higher ed with the addition of several online master’s degrees and a new for-profit college that offers a hybrid of vocational training and liberal arts curriculum online.

Inside Higher Ed reported the nonprofit learning provider edX is offering nine master’s degrees through five U.S. universities — the Georgia Institute of Technology, the University of Texas at Austin, Indiana University, Arizona State University and the University of California, San Diego. The programs include cybersecurity, data science, analytics, computer science and marketing, and they cost from around $10,000 to $22,000. Most offer stackable certificates, helping students who change their educational trajectory.

Former Harvard University Dean of Social Science Stephen Kosslyn, meanwhile, will open Foundry College in January. The for-profit, two-year program targets adult learners who want to upskill, and it includes training in soft skills such as critical thinking and problem solving. Students will pay about $1,000 per course, though the college is waiving tuition for its first cohort.

In the 2030 and beyond world, employers will no longer be a separate entity from the education establishment. Pressures from both the supply and demand side are so large that employers and learners will end up, by default, co-designing new learning experiences, where all learning counts.

OBJECTIVES FOR CONVENINGS

Identify the skills everyone will need to navigate the changing relationship between machine intelligence and people over the next 10-12 years.

Identify a preliminary set of actions that need to be taken now to best prepare for the changing work + learn ecosystem.

Three key questions guided the discussions:

What are the LEAST and MOST essential skills needed for the future?

Where and how will tomorrow’s workers and learners acquire the skills they really need?

Who is accountable for making sure individuals can thrive in this new economy?

This report summarizes the experts’ views on what skills will likely be needed to navigate the work + learn ecosystem over the next 10–15 years—and their suggested steps for better serving the nation’s future needs.

In a new world of work, driven especially by AI, institutionally-sanctioned curricula could give way to AI-personalized learning. This would drastically change the nature of existing social contracts between employers and employees, teachers and students, and governments and citizens. Traditional social contracts would need to be renegotiated or revamped entirely. In the process, institutional assessment and evaluation could well shift from top-down to new bottom-up tools and processes for developing capacities, valuing skills, and managing performance through new kinds of reputation or accomplishment scores.

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In October 2017, Chris Wanstrath, CEO of Github, the foremost code-sharing and social networking resource for programmers today, made a bold statement: “The future of coding is no coding at all.” He believes that the writing of code will be automated in the near future, leaving humans to focus on “higher-level strategy and design of software.” Many of the experts at the convenings agreed. Even creating the AI systems of tomorrow, they asserted, will likely require less human coding than is needed today, with graphic interfaces turning AI programming into a drag-and-drop operation.

Digital fluency does not mean knowing coding languages. Experts at both convenings contended that effectively “befriending the machine” will be less about teaching people to code and more about being able to empathize with AIs and machines, understanding how they “see the world” and “think” and “make decisions.” Machines will create languages to talk to one another.

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Here’s a list of many skills the experts do not expect to see much of—if at all—in the future:

Language translation and localization. This will happen in real time using translator apps.

Legal research and writing. Many of our legal systems will be automated.

Validation skills. Machines will check people’s work to validate their skills.

Driving. Driverless vehicles will replace the need to learn how to drive.

Here’s a list of the most essential skills needed for the future:

Quantitative and algorithmic thinking.

Managing reputation.

Storytelling and interpretive skills.

First principles thinking.

Communicating with machines as machines.

Augmenting high-skilled physical tasks with AI.

Optimization and debugging frame of mind.

Creativity and growth mindset.

Adaptability.

Emotional intelligence.

Truth seeking.

Cybersecurity.

The rise of machine intelligence is just one of the many powerful social, technological, economic, environmental, and political forces that are rapidly and disruptively changing the way everyone will work and learn in the future. Because this largely tech-driven force is so interconnected with other drivers of change, it is nearly impossible to understand the impact of intelligent agents on how we will work and learn without also imagining the ways in which these new tools will reshape how we live.

We just lived through the biggest shift in learning since the printing press—a 25-year shift from print to digital. While it extended access and options to billions, it didn’t prove as transformational as many of us expected. It did, however, set the stage for three shifts that will change what and how people learn.

This emphasis on learning new skills in the age of AI is reinforced by the most recent report on the future of work from McKinsey which suggests that as many as 375 million workers around the world may need to switch occupational categories and learn new skills because approximately 60% of jobs will have least one-third of their work activities able to be automated.

Go scan the job openings and you will likely see many that have to do with technology, and increasingly, with emerging technologies such as artificial intelligence, deep learning, machine learning, virtual reality, augmented reality, mixed reality, big data, cloud-based services, robotics, automation, bots, algorithm development, blockchain, and more.

How many of us have those kinds of skills?Did we get that training in the community colleges, colleges, and universities that we went to?Highly unlikely — even if you graduated from one of those institutions only 5-10 years ago. And many of those institutions are often moving at the pace of a nice leisurely walk, with some moving at a jog, even fewer are sprinting. But all of them are now being asked to enter a race track that’s moving at 180mph. Higher ed — and society at large — are not used to moving at this pace.

This is why I think that higher education and its regional accrediting organizations are going to either need to up their game hugely — and go through a paradigm shift in the required thinking/programming/curricula/level of responsiveness — or watch while alternatives to institutions of traditional higher education increasingly attract their learners away from them.

This is also, why I think we’ll see an online-based, next generation learning platform take place. It will be much more nimble — able to offer up-to-the minute, in-demand skills and competencies.

* Three New HR Roles To Create Compelling Employee Experiences
These new HR roles include:

IBM: Vice President, Data, AI & Offering Strategy, HR

Kraft Heinz Senior Vice President Global HR, Performance and IT

SunTrust Senior Vice President Employee Wellbeing & Benefits

What do these three roles have in common? All have been created in the last three years and acknowledge the growing importance of a company’s commitment to create a compelling employee experience by using data, research, and predictive analytics to better serve the needs of employees. In each case, the employee assuming the new role also brought a new set of skills and capabilities into HR. And importantly, the new roles created in HR address a common vision: create a compelling employee experience that mirrors a company’s customer experience.

An excerpt from McKinsey Global Institute | Notes from the Frontier | Modeling the Impact of AI on the World Economy

Workers.
A widening gap may also unfold at the level of individual workers. Demand for jobs could shift away from repetitive tasks toward those that are socially and cognitively driven and others that involve activities that are hard to automate and require more digital skills.12 Job profiles characterized by repetitive tasks and activities that require low digital skills may experience the largest decline as a share of total employment, from some 40 percent to near 30 percent by 2030. The largest gain in share may be in nonrepetitive activities and those that require high digital skills, rising from some 40 percent to more than 50 percent. These shifts in employment would have an impact on wages. We simulate that around 13 percent of the total wage bill could shift to categories requiring nonrepetitive and high digital skills, where incomes could rise, while workers in the repetitive and low digital skills categories may potentially experience stagnation or even a cut in their wages. The share of the total wage bill of the latter group could decline from 33 to 20 percent.13 Direct consequences of this widening gap in employment and wages would be an intensifying war for people, particularly those skilled in developing and utilizing AI tools, and structural excess supply for a still relatively high portion of people lacking the digital and cognitive skills necessary to work with machines.

Since its inception, Western Governors University (WGU) has aimed to serve learners otherwise shut out of the traditional system. Now, the groundbreaking institution has both graduated 100,000 students and has over 100,000 students currently enrolled. These milestones demonstrate WGU’s ability to scale its high-quality, low-cost model, signaling a momentous shift in the higher education landscape.

In the mid-1990s, governors of 19 states across the western United States were concerned about bringing accessible college education to rural populations, especially working adults.These governors, led by Utah Governor Mike Leavitt, decided to explore building a new university to address the challenge. As the memorandum of understanding between those governors that officially marked the founding of WGU stated, “The strength and well-being of our states and the nation depend increasingly on a strong higher education system that helps individuals adapt to our rapidly changing economy and society. States must look to telecommunications and information technologies to provide greater access and choice to a population that increasingly must have affordable education and training opportunities and the certification of competency throughout their lives.”

Now in its third decade, WGU has students in every U.S. state and has over 100,000 enrolled students—a 230% increase since 2011.

The potential of competency-based education
Competency-based education is an approach to learning that allows students to determine the pace of their learning and move ahead once they demonstrate mastery in a concept. As described by Clayton Christensen and Michelle Weise:

Competency-based programs have no time-based unit. Learning is fixed, and time is variable; pacing is flexible. Students cannot move on until they have demonstrated proficiency and mastery of each competency but are encouraged to try as many times as necessary to demonstrate their proficiency. Although skeptics may question the “rigor” behind an experience that allows students to keep trying until they have mastered a competency, this model is actually far more rigorous than the traditional model, as students are not able to flunk or get away with a merely average understanding of the material; they must demonstrate mastery—and therefore dedicated work toward gaining mastery—in any competency.

Competency-based education first took hold in the K-12 education system, but it is also growing in higher education. As of fall 2015, roughly 600 institutions were using or exploring competency-based programs in higher education.13 However, only a handful of institutions are using competency-based education exclusively and have designed their business models around it.

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WGU offers programs across four industry areas: education, business, information technology, and healthcare. All of these programs are offered online; unlike most higher education institutions, WGU has no physical campus. Instead, it has invested heavily in a technology platform that allows it to deliver curriculum asynchronously, to wherever students are. In addition to its online platform, another unique aspect of WGU’s resources is its approach to faculty. In traditional institutions, faculty are responsible for academic research, course development, teaching, assessment, and advising students. Alternatively, WGU’s model unbundles the faculty role into component parts, with specialists in each role.

A learning ecosystem is a system of people, content, technology, culture, and strategy, existing both within and outside of an organization, all of which has an impact on both the formal and informal learning that goes on in that organization.

The word “ecosystem” is worth paying attention to here. It’s not just there to make the term sound fancy or scientific. A learning ecosystem is the L&D equivalent of an ecosystem out in the wild. Just as a living ecosystem has many interacting species, environments, and the complex relationships among them, a learning ecosystem has many people and pieces of content, in different roles and learning contexts, and complex relationships.

Just like a living ecosystem, a learning ecosystem can be healthy or sick, nurtured or threatened, self-sustaining or endangered. Achieving your development goals, then, requires an organization to be aware of its own ecosystem, including its parts and the internal and external forces that shape them.

From DSC:Yes, to me, the concept/idea of a learning ecosystem IS important. Very important. So much so, I named this blog after it.

Each of us as individuals have a learning ecosystem, whether we officially recognize it or not. So do the organizations that we work for. And, like an ecosystem out in nature, a learning ecosystem is constantly morphing, constantly changing.

We each have people in our lives that help us learn and grow, and the people that were in our learning ecosystems 10 years ago may or may not still be in our current learning ecosystems. Many of us use technologies and tools to help us learn and grow. Then there are the spaces where we learn — both physical and virtual spaces. Then there are the processes and procedures we follow, formally and/or informally. Any content that helps us learn and grow is a part of that ecosystem. Where we get that content can change, but obtaining up-to-date content is a part of our learning ecosystems. I really appreciate streams of content in this regard — and tapping into blogs/websites, especially via RSS feeds and Feedly (an RSS aggregator that took off when Google Reader left the scene).

The article brings up a good point when it states that a learning ecosystem can be “healthy or sick, nurtured or threatened, self-sustaining or endangered.” That’s why I urge folks to be intentional about maintaining and, better yet, consistently enhancing their learning ecosystems. In this day and age where lifelong learning is now a requirement to remain in the workforce, each of us needs to be intentional in this regard.

From DSC:According to the article below, bootcamps appear to be filling several (perceived and/or real) gaps. Quoting from the article:

Why are students enrolling in coding bootcamps? One reason may be the adaptability of these accelerated computer science programs, where students are taught web and mobile development skills that align with industry demands. Programs are offered in-person or online, providing students with flexible learning options. The payoff is decent too: At a typical coding bootcamp, Course Report estimates average tuition is $11,400 for about 14 weeks of instruction, from which the majority students complete on-time and find relevant jobs.

Cost.

Time.

Responsiveness to industry demands.

Greater flexibility.

These are some of the things for traditional institutions of higher education to grapple with, and I would argue the sooner, the better — before this trend finds its legs and gains even more traction/momentum.

For example, in your own mind/thinking…how long do you think it will take bootcamps to begin offering programs that help learners develop content for augmented reality (AR), virtual reality (VR), and mixed reality (MR) — as compared to programs coming out of institutions of traditional higher education?

Whatever your answers are in regards to the reasons for that time difference are likely the exact sort of things institutions need to be working on. For me, at least one of the answers has to do with our current accreditation systems. Other reasons come to my mind as well, but I don’t have time to go there right now.

The five-year coding bootcamp industry estimated at $266 million is rapidly expanding, according to a new market study from Course Report.

The study counted 94 full-time coding bootcamps across the United States and Canada (with programs in 74 U.S. cities). Compared to 2012, there will be 10 times as many graduates this year — or roughly one coding bootcamp graduate for every 3.5 graduates from a traditional university or college. Course Report estimates that 22,814 developers will graduate from coding bootcamps this year — an increase from 15,048 graduates last year.

From DSC:I’ve been thinking about Applicant Tracking Systems (ATSs) for a while now, but the article below made me revisit my reflections on them. (By the way, my thoughts below are not meant to be a slam on Google. I like Google and I use their tools daily.) I’ve included a few items below, but there were some other articles/vendors’ products that I had seen on this topic that focused specifically on ATSs, but I couldn’t locate them all.

In mid-June, Google announced the implementation of an AI-powered search function aimed at connecting job seekers with jobs by sorting through posted recruitment information. The system allows users to search for basic phrases, such as “jobs near me,” or perform searches for industry-specific keywords. The search results can include reviews from Glassdoor or other companies, along with the details of what skills the hiring company is looking to acquire.

As this is a relatively new development, what the system will mean is still an open question. To help, members from the Forbes Coaches Council offer their analysis on how the search system will impact candidates or companies. Here’s what they said…

5. Expect competition to increase. Google jumping into the job search market may make it easier than ever to apply for a role online. For companies, this could likely tax the already strained-ATS system, and unless fixed, could mean many more resumes falling into that “black hole.” For candidates, competition might be steeper than ever, which means networking will be even more important to job search success. – Virginia Franco

10. Understanding keywords and trending topics will be essential.Since Google’s AI is based on crowd-gathered metrics, the importance of keywords and understanding trending topics is essential for both employers and candidates. Standing out from the crowd or getting relevant results will be determined by how well you speak the expected language of the AI. Optimizing for the search engine’s results pages will make or break your search for a job or candidate. – Maurice Evans, IGROWyourBiz, Inc

Before then, 21-year-old Ms. Jaffer had filled out a job application, played a set of online games and submitted videos of herself responding to questions about how she’d tackle challenges of the job. The reason she found herself in front of a hiring manager? A series of algorithms recommended her.

The debate is on, whether man or machine will win the race, as they are pitted against each other in every walk of life. Experts are already worried about the social disruption that is inevitable, as artificial intelligence (AI)-led robots take over the jobs of human beings, leaving them without livelihoods.The same is believed to happen to the HR profession, says a report by Career Builder. HR jobs are at threat, like all other jobs out there, as we can expect certain roles in talent acquisition, talent management, and mainstream business being automated over the next 10 years. To delve deeper into the imminent problem, Career Builder carried out a study of 719 HR professionals in the private sector, specifically looking for the rate of adoption of emerging technologies in HR and what HR professionals perceived about it.

The change is happening for real, though different companies are adopting technologies at varied paces. Most companies are turning to the new-age technologies to help carry out talent acquisition and management tasks that are time-consuming and labor-intensive.

From DSC: Are you aware that if you apply for a job at many organizations nowadays, your resume has a significant chance of not ever making it in front of a human’s eyeballs for their review? Were you aware that an Applicant Tracking System (an ATS) will likely syphon off and filter out your resume unless you have the exact right keywords in your resume and unless you mentioned those keywords the optimal number of times?

And were you aware that many advisors assert that you should use a 1 page resume — a 2 page resume at most? Well…assuming that you have to edit big time to get to a 1-2 page resume, how does that editing help you get past the ATSs out there? When you significantly reduce your resume’s size/information, you hack out numerous words that the ATS may be scanning for. (BTW, advisors recommend creating a Wordle from the job description to ascertain the likely keywords; but still, you don’t know which exact keywords the ATS will be looking for in your specific case/job application and how many times to use those keywords. Numerous words can be of similar size in the resulting Wordle graphic…so is that 1-2 page resume helping you or hurting you when you can only submit 1 resume for a position/organization?)

Vendors are hailing these ATS systems as being major productivity boosters for their HR departments…and that might be true in some cases. But my question is, at what cost?

At this point in time, I still believe that humans are better than software/algorithms at making judgement calls. Perhaps I’m giving hiring managers too much credit, but I’d rather have a human being make the call at this point. I want a pair of human eyeballs to scan my resume, not a (potentially) narrowly defined algorithm. A human being might see transferable skills better than a piece of code at this point.

Just so you know…in light of these keyword-based means of passing through the first layer of filtering, people are now playing games with their resumes and are often stretching the truth — if not outright lying:

Employer Applicant Tracking Systems Expect an Exact MatchMost companies use some form of applicant tracking system (ATS) to take in résumés, sort through them, and narrow down the applicant pool. With the average job posting getting more than 100 applicants, recruiters don’t want to go bleary-eyed sorting through them. Instead, they let the ATS do the dirty work by telling it to pass along only the résumés that match their specific requirementsfor things like college degrees, years of experience, and salary expectations. The result? Job seekers have gotten wise to the finicky nature of the technology and are lying on their résumés and applications in hopes of making the cut.

From DSC:
I don’t see this as being very helpful. But perhaps that’s because I don’t like playing games with people and/or with other organizations. I’m not a game player. What you see is what you get. I’ll be honest and transparent about what I can — and can’t — deliver.

But students, you should know that these ATS systems are in place. Those of us in higher education should know about these ATS systems, as many of us are being negatively impacted by the current landscape within higher education.

Is Your Resume ATS Friendly?
Did you know that an ATS (applicant tracking system) will play a major role in whether or not your resume is selected for further review when you’re applying to opportunities through online job boards?

It’s true. When you apply to a position a company has posted online, a human usually isn’t the first to review your resume, a computer program is. Scouring your resume for keywords, terminology and phrases the hiring manager is targeting, the program will toss your resume if it can’t understand the content it’s reading. Basically, your resume doesn’t stand a chance of making it to the next level if it isn’t optimized for ATS.

To ensure your resume makes it past the evil eye of ATS, format your resume correctly for applicant tracking programs, target it to the opportunity and check for spelling errors. If you don’t, you’re wasting your time applying online.